Task-oriented dialogue systems aim to assist users to accomplish a task (e.g. booking a flight, making a restaurant reservation and playing a song) through dialogue in natural language, either in a spoken or written form.
As in most of the current approaches, we assume a system involving a pipeline of components [1]}, where the user utterance is first processed by an Automatic Speech Recognition (ASR) module and then
processed by a Natural Language Understanding (NLU) component, which interprets the user's needs. Then a Dialogue State Tracker (DST) accumulates the dialogue information as the conversation progresses and may query a domain knowledge base to obtain relevant data. A dialogue policy manager then decides what is the next action to be executed and a Natural Language Generation (NLG) component produces the actual response to the user.
